1. Field of the Invention
The present invention relates to a charging control system and a charging control method that applies to vehicles that run on electricity, the vehicles including hybrid type vehicles that are equipped with an non-electric power source.
2. Description of the Related Art
In that serious concern is being focused on environmental problems in recent years, it is thought that renewable power supplies such as photovoltaic power generator and wind power generators that are being rapidly implemented will become effective means to achieve low carbon society and solve energy resource problems. On the other hand, however, since such renewable power supplies have large output fluctuations, adjustment means need to be provided that offsets their output fluctuations from the standpoint of supplying quality power. To date, since thermal generators that have high response speeds have been implemented as the adjustment means, this results in a dilemma in which as renewable power supplies are increasingly implemented, more thermal power generators are needed as adjustment means. Thus, it will become an important problem to ensure alternative powerful adjustment means. Although it might be effective means to implement large capacity rechargeable batteries such as NaS batteries, they would have a very high implementation barrier from the implementation and operation cost perspectives.
V2G (Vehicle-to-Grid) techniques that cause rechargeable batteries equipped in vehicles, that run on electricity and that are expected to be rapidly popularized (hereinafter, these vehicles including hybrid type vehicles equipped with a non-electric power source are referred to as EVs (Electric Vehicles)) and chargers connected thereto to be linked, and to be used them as a virtual large capacity rechargeable battery that would stabilize the power system have been studied. V2G has been proposed since 1980s and research including estimation of macroscopic stabilization effects of the entire electric power grid have been continuously reported up to the present. In recent several years, microscopic control techniques that are used in the manufacturing of specific systems, namely those that individually control charging and discharging of many EVs in real time have been reported.
Examples include, Non-patent Literature 1 (G. K. Venayagamoorthy et. al., “Real-Time Modeling of Distributed Plug-in Vehicles for V2G Transactions,” Energy Conversion Congress and Exposition, 2009. ECCE 2009. IEEE, 3937-3941 (2009)) presents a charging and discharging control method that performs optimum scheduling based on Particle Swarm Optimization (PSO) that sets up EV operation models, electric power grid models, time variation models of electric power prices, and so forth and that was inspired by movement of a shoal of fish.
Patent Literature 1 (JP2000-20977A, Publication) describes a configuration of an EV charging scheduling device and also mentions optimum charging schedule based on a genetic algorism.
Patent Literature 2 (JP2010-213560A, Publication) describes a configuration that stably charges an EV using a stationary rechargeable battery that serves as an electric power buffer connected in series between the electric power grid and the EV without necessity to expand the capacity of the electric power grid side infrastructure.
Although a configuration that is expected not only to charge an EV with electricity but also to discharge it from the EV to the electric power grid side is also referred to as V2G, a configuration that is expected only to charge the EV with electricity might be referred to as G2V so as to distinguish itself from V2G. G2V would reduce the load imposed on the internal rechargeable battery provided in each EV because of a decrease in charging and discharging cycles.
However, to date, few practical systems that comprehensive evaluate the reduction of load and risk (imperfect charging upon departure and accelerated deterioration of rechargeable battery of EV) imposed on EVs' owners, the quality of grid stabilization service, real time response, decrease of load imposed on computational processes for optimum scheduling, and so forth have been reported. Thus, this situation has bottlenecked the implementation of multiple EVs linked to a charging control system.
Next, realistic problems with respect to charging schedule for EVs will be described.
As a first problem, if connection times at which EVs are connected to chargers (electric power grid) at daytime at temporary parking lots largely fluctuate and if their connection times are unexpectedly short, the charging schedule will not be implemented exactly as planned, and this will result in EVs that are not fully charged. Even if arrival times and departure times of EVs can be completely ensured, if the connection times are too short, since the degree of freedom with respect to shifting charging times is low, charging demands that occur in EVs would not be almost effectively used to stabilize the electric power grid and thereby they would be expected to simply become temporal peak noise of electric power demands or could concentrate to a time zone in which charge connection times are long (for example, nighttime).
As a second problem, in a transitional period of popularization of EVs or if EV use times are irregularly patterned, since few or no EVs are connected to chargers (electric power grid), a time zone in which charging control can hardly be performed, namely, power demands that serve as an electric power adjustment capability are not supplied to the electric power supply (electric company) side, (this time zone is referred to as a dead time) could occur. In addition, before and after the dead time, since the number of EVs connected to the chargers (electric power grid) is small, it is likely that the load (rapid charging, imperfect charging, and so forth) concentrates on particular EVs.
FIG. 1a exemplifies a dead time that occurs in an ordinary multiple EV linked charging system and shows charger connection states that are generated at random for 50 EVs that are used for commuting for three days (one holiday and two weekdays). FIG. 1b exemplifies dead times that occur in an ordinary multiple EV linked charging system and shows that charging scheduling is performed such that charging demands of all EVs that arrived are adjusted in chronological order in the time zone in which the EVs stopped.
As shown in FIG. 1a, when EVs are not connected to chargers, they are running, namely they are consuming electric power. In FIG. 1a, the amounts of stored electricity of individual EVs at the beginning of the first day were randomly generated.
As shown in FIG. 1b, in a time zone in which EVs are running, namely they are not connected to chargers, dead times in which electric power (charging) demands cannot be controlled occur.
In the configuration described in Patent Literature 2, since a stationery rechargeable battery is connected in series between the electric power grid and the EV side, electric power supplied from the electric power grid is temporarily stored in the stationary rechargeable battery, and all EVs are charged with electricity through the stationary rechargeable battery, it would be necessary to provide a large capacity rechargeable battery that satisfies charging demands of nearly all the EVs although it would not be necessary to increase the rated capacity of an electric power system that is superior to the stationary rechargeable battery. Thus, it could be expected that both the initial cost and operation cost would remarkably increase.
Since charging demands that EVs create have the potential to prevent electric power demands from being forcibly created so as to stabilize the electric power grid, namely to prevent energy resources from being wasted and thereby to effectively use the saved energy for others. Thus, the charging demands of EVs could be considered to be a kind of “energy resources.” In this context, latent electric power demands for the electric power grid that can chronologically shift demands to some extent are defined as electric power charging demand potentials.